International Journal of Scientific and Research Publications, Volume 2, Issue 8, August 2012
ISSN 2250-3153
1
FAME and 16srDNA sequence analysis of halophilic
bacteria from solar salterns of Goa: A comparative study
Surve V V*, Patil M U**, Dharmadhikari S M***
*
Department of Biotechnology, Vivekanand College
**
Department of Zoology, Dr.BAMU
***
Department of Microbiology, Institute of Science Aurangabad, Maharashtra, 431001 India
Abstract- Halophilic microorganisms present in the
hypersaline environments of solar salterns present a potential
source of industrial and biotechnological applications .The Rapid
identification of these microorganisms which are accurate and
cost effective is a necessity in applied microbiology. There have
been several systems developed in the past few years for rapid
microbial identification. In the present study, GC FAME( Gas
chromatography- Fatty acid methyl esters) analysis and 16s
rDNA sequencing were compared for identification of four
halophilic bacteria. Four halophilic bacterial isolates obtained
from solar saltern sediment were analyzed . The isolates were
identified with 16srDNA sequencing
as
Virgibacillus
pantothenticus,
Bacillus
atrophaeus,
Corynebacterium
diphtheria and ,Idiomarina Zobellii
.However in FAME
analysis , the RTBSA 6 library did not confirm any matches
for Idiomarina Zobellii. Comparative analysis, indicated that
the FAME analysis results correlates to genotypic sequencing
results. However,a halophilic bacterial FAME library should be
established to enhance the accurate , rapid and cost effective
investigation of halophilic microorganisms.
Index Terms- Solar salterns, Halophilic bacteria, FAME,
Sequencing, BLAST, Identification
I. INTRODUCTION
D
etermining the taxonomic composition, biomass, and
physiological status of microbial assemblages is still one of
the greatest challenges facing ,microbial ecologists. Classical
approaches that utilize enrichment methods for the isolation of
microorganisms from the environment continue to provide
valuable information in biochemical, taxonomic, and
autoecological studies. The primary limitations to such
approaches are those of non culturability ,and the problem of
characterizing and identifying statistically relevant numbers of
isolates necessary to gain insight into the population ecology and
community diversity of habitats(Thompson et al., 1999). Rapid
and accurate identification of bacterial pathogens is a
fundamental goal of clinical microbiology, but one that is
difficult or impossible for many slow-growing and fastidious
organisms(Tang, 1998).New and exciting molecular methods,
using the 16S small sub-unit ribosomal nucleic acid molecules
have added much to our knowledge of microbial diversity
(Macrae A ,2000). For many years, sequencing of the 16S
ribosomal RNA (rRNA) gene has
shown that sequence
identification is useful for slow-growing, unusual, and fastidious
bacteria as well as for bacteria that are poorly differentiated by
conventional methods. The technical resources necessary for
sequence identification are significant. Despite the availability of
resources, sequence-based identification is still relatively
expensive(Patel 2001).Although it is generally regarded that
routine identification of very common species using conventional
methodologies
are highly accurate, we now have a more
convenient and precise mechanism for checking these
identifications on a molecular basis. Such studies need to be
performed and published( Janda , 2007).The 16S rDNA
sequence analysis is the reliable method for halophilic bacterium
identification.(Chookiwattana,2003).Recent advances in the
biochemistry of microorganisms revealed that analysis of cell
components, such as proteins and fatty acids, can be effectively
applied to bacterial identification, providing the basis for
chemotaxonomy(Goodfellow, 1985., Komagata,
1987).Fatty
acids are one of the most important building blocks of cellular
materials. In bacterial cells, fatty acids occur mainly in the cell
membranes as the acyl constituents of phospholipids. These
fatty acids are synthesized in certain bacteria from iso, anteiso, or
cyclic primer and malonyl-CoA with or without a subsequent
modification( Kaneda, 1977.,Lechevalier 1977. ,Wilkinson
1988).The occurrence of branched-chain fatty acids as major
constituents in bacteria was first reported for Bacillus
subtilis(Saito, K. 1960. )These days, fatty acids in bacterial lipids
are routinely analyzed by gas-liquid chromatography. In
addition, other methods such as nuclear magnetic resonance
spectroscopy,infrared spectroscopy, mass spectrometry, and thinlayer chromatography have been used to aid the gas-liquid
chromatographic identification of fatty acids ( Toshi 1991 ).The
unique pattern of fatty acids in bacteria is the basis of
identification in FAME analysis.The MIDI (Microbial
Identification Incorporation) Sherlock FAME analysis is a
laboratory-based system that can be used on a routine basis to
identify commonly isolated bacteria from clinical and
environmental source( Leonard et al 1995) More than 300 fatty
acids and related compounds have been found in bacteria are
analyzed in the MIDI Research and Development Laboratory.
Whole cell fatty acids are converted to methyl esters and
analyzed by gas chromatography. The fatty acid composition of
the unknown is compared to a library of known organisms in
order to find the closest match. The peaks are automatically
named and quantitated by the system .Branched chain acids
predominate in some Gram positive bacteria, while short chain
hydroxy acids often characterize the lipopolysaccharides of the
Gram negative bacteria(Sasser, 2001) . The MIS, as the first
automated CFA(Cellular fatty acid ) identification system, is an
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International Journal of Scientific and Research Publications, Volume 2, Issue 8, August 2012
ISSN 2250-3153
accurate, efficient, and relatively rapid method for the
identification of microorganisms ( Osterhout et al 1991).The
identification of marine isolates, is a continuing challenge for
marine microbiologists. The identification of marine bacteria is
commonly based on a wide range of biochemical and
physiological tests. The major difficulties found with this
traditional approach are the need for an easily cultivable strain
and the time required for the preparation of cultures (AkagawaMatsushita, et al., 1992) Solar saltpans are found worldwide and
are considered extreme environments with very restricted
biology (Litchfield, 2002).It is surmised that marine
environments like solar saltern may yield newer strains which
may prove to be a rich resource of new metabolites.
Microorganisms that thrive in these hypersaline environments
are called halophilic microorganisms (that is, require salt for
their viability .The domain bacteria typically contains many
types of halophilic microorganisms that spread over a large
number of phylogenetic subgroups and they are moderate rather
than extreme halophiles (Oren, 2002).
Sparked by the
availability of microbial diversity data in these salterns an effort
is made to study the moderately halophilic bacterial in these
extreme environments. The bacteria are analyzed for their
identity by two methods 16s rDNA sequencing and GCFAME,.The similarity between these methods is comparatively
studied.
II. MATERIALS AND METHOD
Four
halophilic bacterial pure cultures were obtained
from solar saltern sediment and designated as H1, H2, H3 and H
4 .The cultures were grown on halophile medium(10% salt) at
28°C for 48-72 hours. The fatty acids were extracted and
methylated to form fatty acid methyl esters (FAME). These
FAME’s were analyzed using Gas Chromatography with the help
of MIDI Sherlock software for FAME. Aerobic library (RTBSA
6.0) was referred for the analysis. The analysis was performed as
per (Sasser, 2001).
For 16s rDNA sequence analysis the
genomic DNA was isolated. PCR amplifications of the 16S
rRNA gene, from the purified genomic DNAs, were carried out
using the primer sets 27F (5´AGAGTTTGATCCTGGCTCAG3´) and1492R (5´-GGTTACCTTGTTACGACTT-3´). The
amplified DNA was purified and sequencing of the target gene
was done using Big Dye Chemistry, and performed as per the
manufacturer's protocols (Applied Biosystems ). The purified
extension products were separated in the ABI 3730xl DNA
Analyzer by capillary electrophoresis. Sequence data analysis
was done using ChromasPro and Sequencing Analysis software.
The bioinformatics analysis was performed using NCBI BLAST
(http://ncbi.nlm.nih.gov/blast) identifying the microorganism
using online databases. The analysis data from the Sequencing
and FAME analysis obtained was comparatively studied.
III. RESULTS
The four halophilic microbial cultures obtained from saltern
sediment were analyzed using FAME and sequencing
approaches. On comparing FAME results with that of
sequencing, it was found that both the methods correlate to each
2
other in confirmation of identity
of the isolates except for
isolate H4. Figure 1 shows peaks corresponding to the fatty
acids identified through FAME analysis of bacterial sample H1.
The MIDI Sherlock microbial identification system using
RTSBA6 method identified the organism to be Corynebacterium
diptheriae with 0.596 Similarity index(SI). The sequence
analysis also showed similar results (Table 1). After the
completion of BLAST analysis the organism was identified to
Corynebacterium diphtheriae strain with 73% identity match.
FAME analysis identified H2 as Virgibacillus Pantothenticus
with similarity index 0.698(Figure 2).Sequence analysis allied
with this identification ,as the after BLAST analysis the isolate
H2 was identified as Virgibacillus Pantothenticus
strain
OLO3.(Table 2).The methods also displayed parallel results for
isolate H3. Wherein the H3 isolate was identified as Bacillus
atrophaeus with FAME analysis (Similarity index 0.776. (Figure
3).The sequencing and BLAST identified the isolated as Bacillus
atrophaeus with 100% identity match. However the isolate H4,
identified as Idiomarina Zobellii
100 % identity match after
BLAST analysis, did not find any matching chromatogram
pattern in FAME RTBSA6 6.0 aerobic library.
IV. DISCUSSION
Identification of bacteria by conventional methods usually
requires ≥48 h after a colony has been isolated. The identification
of slow-growing or biochemically inert microbes to the species
level is difficult and time-consuming by conventional methods.
16S rRNA gene sequences frequently provide phylogenetically
useful information. Signature nucleotides allow classification
even if a particular sequence has no match in the database, since
otherwise-unrecognizable isolates can be assigned to a
phylogenetic branch at the class, family, genus, or subgenus
level. Cost is a critical issue in the evaluation of 16S rDNA
sequence analysis as a diagnostic tool. However, sequencing
costs will probably continue their rapid trend downward,
bringing this technology within the reach of many microbiology
laboratories (Tang, 1998). Roohi et al in 2012 studied the
halotolerant and Halophilic bacteria from salt mines of karak,
Pakistan with 16S rRNA gene sequence.As the phenotypic
characteristics alone were not enough to differentiate the
bacterial isolates and could lead to identification problems. The
main reason for this is the standardization of a conventional
method, when it was applied to halophilic bacteria because their
growth characteristic highly dependent on many factors such as
NaCl concentrations, temperature, pH and medium
composition.All the four isolates were sucessfully sequenced and
identified in the present study.The MIDI FAME system
identified 3 out of 4 bacterial isolates to the correct species
level. The results were in accordance to the findings of
Chookiewattana K, 2003 .Wherein 14.1% of halophilic bacterial
isolates were not identified by FAME analysis, differing the
100% identification by 16srDNA sequencing. Species level
identification of microbes is possible through MIDI Sherlock
microbial identification. Abel and colleagues first suggested
that microorganisms could be classified by gas chromatographic
analysis (Abel et al 1963). The Sherlock Microbial Identification
System is an accurate and automated gas chromatographic
system, which identifies over 1,500 bacterial species based on
their unique fatty acid profiles. The system can analyze over 200
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International Journal of Scientific and Research Publications, Volume 2, Issue 8, August 2012
ISSN 2250-3153
samples per day,uses a standardized sample procedure for all
bacteria, and costs about $2.50 per sample in standard laboratory
consumables (Sasser M 2001) .The MIDI’s identification was
listed with a confidence measurement (similarity index [SI]) on a
scale of no match to 0.965.The Sherlock microbial identification
system is solely based on computer comparison of the unknown
organism's fatty acid methyl ester profile with the profiles of a
predetermined library of known isolates with pattern recognition
software (Tang et al 1998).The fatty acid analysis by the MIDI
system can be a useful supplement and reference method, but
cannot be recommended at this time for the routine identification
of halophilic bacteria until a library of halophilic bacterium
isolates is established in the MIDI database.
Presently, the
MIDI system does not contain a library for halophilic bacteria.
The database RTBSA6 is the closet database for halophilic
bacteria (Chookiewattana , 2003). The data and isolate obtained
in this study can be used to develop the database in the MIDI
system library for future identification of halophilic bacteria. The
halophilic library can be constructed with ease as halophiles are
studied extensively throughout the world . Recently marine red
pigmented Bacteria isolated from nellore costal region of andhra
Pradesh were studied for their fatty acid profile by FAME
Accession
FJ409575.1
FJ409574.1
FJ409573.1
FJ409572.1
3
analysis(pabba et al .,2011). Similarly the fatty acid methyl
esther profiles of 6 isolates belonging to bacteria domain
representing different genera and species were analyzed by
Guvenk et al in 2010.
V. CONCLUSION
Therefore, through the above study we can conclude that
FAME analysis and 16s rDNA sequencing are rapid and accurate
methods for bacterial identification .FAME analysis has an
added advantage of being cost effective as compared to
sequencing. Thus this technology should be implemented by
microbiologists
into routine practice. However, the MIDI
FAME libraries should be upgraded with chromatogram profiles
of more micro-organisms. As halophiles from extreme
environments like solar salterns of Goa, are potential candidates
for enzymatic and other industrial applications, a library of
halophilic microbes should be established.The halophilic
microbial library can assist faster and accurate identification of
novel halophiles.
Description
Corynebacterium diphtheriae
CD450 16S ribosomal RNA
partial sequence
Corynebacterium diphtheriae
CD449 16S ribosomal RNA
partial sequence
Corynebacterium diphtheriae
CD448 16S ribosomal RNA
partial sequence
Max
score
Total
score
Max
ident
strain
gene, 206
206
73%
strain
gene, 206
206
73%
strain
gene, 206
206
73%
206
73%
Corynebacterium diphtheriae strain
CD443 16S ribosomal RNA gene, 206
partial sequence
Corynebacterium diphtheriae VA01,
195
975
73%
complete genome
Corynebacterium diphtheriae HC04,
CP003215.1
195
975
73%
complete genome
Corynebacterium diphtheriae HC03,
CP003214.1
195
975
73%
complete genome
Table 1: Blast Similarity Search Results fo H1 :Similarity to Corynebacterium diphtheriae strain CD450 by 16S ribosomal
rRNAgene, partial sequence.
CP003217.1
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International Journal of Scientific and Research Publications, Volume 2, Issue 8, August 2012
ISSN 2250-3153
4
1.800
140
3.260
0.743
0.750
2.700
FID1 A, (E12330.416\A0060003.D)
pA
3.324
120
100
0.5
1
1.5
2
2.5
3
Library
Sim Index
Entry Name
RTSBA6 6.00
0.596
Corynebacterium diphtheriae
3.5
4
4.132
4.180
4.224
3.391
3.468
3.517
3.539
3.564
3.580
3.631
3.690
3.767
3.799
3.851
3.867
3.883
3.900
3.932
4.003
2.191
2.280
2.308
2.366
2.390
2.446
2.518
2.549
2.584
2.612
2.635
2.649
2.682
2.726
2.783
2.799
2.829
2.843
2.857
2.873
2.897
2.928
2.953
2.986
3.012
3.085
3.145
3.168
3.212
3.226
3.276
1.873
1.898
1.990
2.015
2.071 2.093
1.166
60
1.535
1.568
1.073
80
m in
Figure 1: Chromatogram of bacterial sample H1 showing the fatty acid peaks through Agilent GC 6850.
Accession
JN791392.1
AB617570.1
AB305195.1
AB196352.1
AB681789.1
AB489108.1
AB039331.1
Description
Virgibacillus pantothenticus strain OL03
16S ribosomal RNA gene, partial sequence
Virgibacillus pantothenticus gene for 16S
rRNA, partial sequence, isolate: T8-4T
Virgibacillus pantothenticus gene for 16S
rRNA, partial sequence
Virgibacillus pantothenticus gene for 16S
rRNA, partial sequence, strain:PS11
Virgibacillus pantothenticus gene for 16S
rRNA, partial sequence, strain: NBRC
102447
Virgibacillus pantothenticus gene for 16S
rRNA, partial sequence
Virgibacillus pantothenticus gene for 16S
rRNA, strain:M1-4
Max
score
Total
score
Max
ident
1483
1483
88%
1483
1483
88%
1483
1483
88%
1483
1483
88%
1456
1456
88%
1456
1456
88%
1447
1447
88%
Table2: Blast Similarity Search Results for H2:Similarity to Virgibacillus pantothenticus 16S ribosomal RNA gene, partial
sequence
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International Journal of Scientific and Research Publications, Volume 2, Issue 8, August 2012
ISSN 2250-3153
5
0.750
2.312
FID1 A, (E12328.590\A0200016.D)
pA
130
120
2.933
110
0.5
1
1.5
2
2.5
Library
Sim Index
Entry Name
RTSBA6 6.00
0.698
Virgibacillus pantothenticus
3
3.5
3.801
3.846
3.858
3.904
3.942
4.002
4.041
4.081
4.095
4.138
3.217
3.235
3.264
3.280
3.329
3.353
3.399
3.420
3.472
3.522
3.542
3.588
3.629
3.681
2.902
2.394
2.412
2.461
2.521
2.573
2.615
2.635
2.653
1.725
1.748
1.803
50
1.489
1.569
1.188
60
2.020 1.993
2.096
70
3.018
3.090
2.590
80
2.804
2.862
90
2.703
2.284
100
4
m in
Figure 2: Chromatogram of bacterial sample H2 showing the fatty acid peaks through Agilent GC 6850.
Accession
Description
Max
score
Total
score
Max
ident
Bacillus atrophaeus strain BF 3fF 16S
473
2196
100%
ribosomal RNA gene, partial sequence
Bacillus atrophaeus strain ZaK 16S
JN824998.1
473
1604
100%
ribosomal RNA gene, partial sequence
Bacillus atrophaeus gene for 16S rRNA,
AB681057.1
473
2196
100%
partial sequence, strain: NBRC 16183
Bacillus atrophaeus gene for 16S rRNA,
AB680855.1
473
2202
100%
partial sequence, strain: NBRC 15407
Bacillus atrophaeus gene for 16S rRNA,
partial sequence, strain: NBRC 13721
AB680488.1
>dbj|AB680560.1| Bacillus atrophaeus 473
2196
100%
gene for 16S rRNA, partial sequence,
strain: NBRC 14117
Bacillus atrophaeus strain LLS-M3-4 16S
HM744708.1
473
2191
100%
ribosomal RNA gene, partial sequence
Bacillus atrophaeus strain KM40 16S
JF411316.1
473
2196
100%
ribosomal RNA gene, partial sequence
Table 3: Blast Similarity Search Results for H3:Similarity to Bacillus atrophaeus strain BF 3fF 16S ribosomal RNA gene,
partial sequence
JQ693811.1
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International Journal of Scientific and Research Publications, Volume 2, Issue 8, August 2012
ISSN 2250-3153
6
2.872
0.732
2.259
FID1 A, (E12508.678\A0190013.D)
pA
2.231
90
80
70
60
1
1.5
2.5
3
3.800
3.860
3.896
3.952
3.991
4.045
3.198
3.245
3.265
3.355
3.435
3.489
3.510
3.546
3.593
3.612
3.658
3.698
2.956
2.561
2.577
2.340
2.357
2.380
2.406
2.465
1.9701.944
2.047
1.703
1.755
2
2.773
2.802
2.533
0.5
1.529
1.003
20
1.100
30
2.646
40
2.842
50
3.5
m in
4
Figure 3: Chromatogram of bacterial sample H3 showing the fatty acid peaks through Agilent GC 6850.
Library
Sim Index
Entry Name
RTSBA6 6.00
0.776
Bacillus atrophaeus
Accession
GU397379.1
AB619724.2
EU440964.1
EU305725.1
DQ985042.1
DQ235548.1
AY553079.1
Description
Idiomarina zobellii strain G5B 16S
ribosomal RNA gene, partial sequence
Idiomarina sp. TPS4-2 gene for 16S
ribosomal RNA, partial sequence, strain:
TPS4-2
Idiomarina seosinensis strain PR58-8 16S
ribosomal RNA gene, partial sequence
Idiomarina sp. TBZ1 16S ribosomal RNA
gene, partial sequence
Idiomarina sp. JL974 16S ribosomal RNA
gene, partial sequence
Bacterium ABKPF4 16S ribosomal RNA
gene, partial sequence
Idiomarina loihiensis strain GSP37 16S
ribosomal RNA gene, partial sequence
Max
score
Total
score
Max
ident
592
2631
100%
588
3582
100%
588
3617
100%
588
3663
100%
588
3582
100%
588
3542
99%
588
3511
100%
Table 4: Blast Similarity Search Results for H4:Similarity to Idiomarina zobellii strain G5B 16S ribosomal RNA gene, partial
sequence
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International Journal of Scientific and Research Publications, Volume 2, Issue 8, August 2012
ISSN 2250-3153
7
0.732
2.233
FID1 A, (E12508.678\A0110007.D)
pA
250
2.844
200
150
0.5
1
1.5
2
2.5
3.5
4.042
4.120
4
4.241
3.117
3
3.153
3.201
3.217
3.235
3.266
3.292
3.324
3.369
3.401
3.437
3.460
3.477
3.514
3.548
3.570
3.594
3.656
3.701
3.730
3.761
3.804
3.843
3.870
3.896
2.782
2.816
2.873
2.899
2.957 2.929
2.985
2.497
2.534
2.584
2.596
2.627
2.647
2.671
2.698
1.257
1.322
1.343
1.415
1.450
1.492
1.530 1.557
1.577
1.632
1.644
1.681
1.703
1.756
1.814
1.906
1.945
1.997
2.033
2.047
2.087
2.175
2.194
2.259
2.316
2.341
2.386
50
1.097
1.155
1.179
0.798
100
m in
Figure 4 : Chromatogram of bacterial sample H4showing the fatty acid peaks through Agilent GC 6850.
No matches found in RTBSA6 6.0 Library
ACKNOWLEDGMENT
We are thankful to Dr Sameer Damare Scientist, NIO, Goa and
Royal life science laboratory , Secunderabad India for the
support and guidance.
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AUTHORS
First Author – Vaishali V Surve , Department of
Biotechnology, Vivekanand college Aurangabad ,Maharashtra
431001 India. E-mail id- [email protected]
www.ijsrp.org
International Journal of Scientific and Research Publications, Volume 2, Issue 8, August 2012
ISSN 2250-3153
Second Author – Dr.(Mrs)Meena U Patil, ,Professer,
Department of Zoology, Dr.BAMU Aurangabad ,Maharashtra
[email protected]
Third Author – Dr. (Smt.) S.M. Dharmadhikari, Govt. Institute
of Science, Nipat Niranjan Road, Aurangabad. Maharashtra
431001
8
Correspondence Author – Miss Vaishali V Surve , Department
of Biotechnology, Vivekanand college Aurangabad ,Maharashtra
431001 India . E-mail id- [email protected]
Mob: 91 9226858066
www.ijsrp.org